Dispersed storage write process with lock/persist

ABSTRACT

A method begins by one or more processing modules of one or more computing devices of a dispersed storage network (DSN) determining that dispersed error encoded data slices stored in a plurality of distributed storage units of the DSN are to be updated and then sending a plurality of lock requests respectively to the plurality of distributed storage units. The method continues with the processing modules receiving a response from a write threshold number of distributed storage units of the plurality of distributed storage units that a lock request has been granted by each of the write threshold number of distributed storage units and then sending a persist message to each of the write threshold number of distributed storage units from which the lock request has been granted.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not applicable.

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not applicable.

BACKGROUND OF THE INVENTION Technical Field of the Invention

This invention relates generally to computer networks and moreparticularly to dispersing error encoded data.

Description of Related Art

Computing devices are known to communicate data, process data, and/orstore data. Such computing devices range from wireless smart phones,laptops, tablets, personal computers (PC), work stations, and video gamedevices, to data centers that support millions of web searches, stocktrades, or on-line purchases every day. In general, a computing deviceincludes a central processing unit (CPU), a memory system, userinput/output interfaces, peripheral device interfaces, and aninterconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using“cloud computing” to perform one or more computing functions (e.g., aservice, an application, an algorithm, an arithmetic logic function,etc.) on behalf of the computer. Further, for large services,applications, and/or functions, cloud computing may be performed bymultiple cloud computing resources in a distributed manner to improvethe response time for completion of the service, application, and/orfunction. For example, Hadoop is an open source software framework thatsupports distributed applications enabling application execution bythousands of computers.

In addition to cloud computing, a computer may use “cloud storage” aspart of its memory system. As is known, cloud storage enables a user,via its computer, to store files, applications, etc. on an Internetstorage system. The Internet storage system may include a RAID(redundant array of independent disks) system and/or a dispersed storagesystem that uses an error correction scheme to encode data for storage.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a dispersed ordistributed storage network (DSN) in accordance with the presentinvention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present invention;

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data in accordance with the present invention;

FIG. 4 is a schematic block diagram of a generic example of an errorencoding function in accordance with the present invention;

FIG. 5 is a schematic block diagram of a specific example of an errorencoding function in accordance with the present invention;

FIG. 6 is a schematic block diagram of an example of a slice name of anencoded data slice (EDS) in accordance with the present invention;

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of data in accordance with the present invention;

FIG. 8 is a schematic block diagram of a generic example of an errordecoding function in accordance with the present invention;

FIG. 9 is a diagram of an example of a distributed storage and taskprocessing in accordance with the present invention;

FIG. 10A is a diagram of an embodiment of a structure of a large dataobject in accordance with the present invention;

FIG. 10B is a diagram of an embodiment of a structure of a data objectstorage tracking table in accordance with the present invention;

FIG. 10C is a schematic block diagram of an embodiment of a dispersedstorage network (DSN) in accordance with the present invention;

FIG. 10D is a diagram of an example of writing data regions inaccordance with the present invention;

FIG. 10E is a diagram of an example of writing a data region inaccordance with the present invention;

FIG. 10F-J are diagrams of an embodiment of a dispersed storage network(DSN) illustrating steps of an example of writing data in accordancewith the present invention;

FIG. 11 is a flowchart illustrating an example of writing a data objectin accordance with the present invention;

FIG. 12 is a flowchart illustrating an example of overwriting a dataobject in accordance with the present invention;

FIG. 13 is a flowchart illustrating an example of updating a data objectin accordance with the present invention;

FIG. 14 is a schematic block diagram of an example of updating data inaccordance with the present invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a dispersed, ordistributed, storage network (DSN) 10 that includes a plurality ofcomputing devices 12-16, a managing unit 18, an integrity processingunit 20, and a DSN memory 22. The components of the DSN 10 are coupledto a network 24, which may include one or more wireless and/or wirelined communication systems; one or more non-public intranet systemsand/or public internet systems; and/or one or more local area networks(LAN) and/or wide area networks (WAN).

The DSN memory 22 includes a plurality of storage units 36 that may belocated at geographically different sites (e.g., one in Chicago, one inMilwaukee, etc.), at a common site, or a combination thereof. Forexample, if the DSN memory 22 includes eight storage units 36, eachstorage unit is located at a different site. As another example, if theDSN memory 22 includes eight storage units 36, all eight storage unitsare located at the same site. As yet another example, if the DSN memory22 includes eight storage units 36, a first pair of storage units are ata first common site, a second pair of storage units are at a secondcommon site, a third pair of storage units are at a third common site,and a fourth pair of storage units are at a fourth common site. Notethat a DSN memory 22 may include more or less than eight storage units36. Further note that each storage unit 36 includes a computing core (asshown in FIG. 2, or components thereof) and a plurality of memorydevices for storing dispersed error encoded data.

Each of the computing devices 12-16, the managing unit 18, and theintegrity processing unit 20 include a computing core 26, which includesnetwork interfaces 30-33. Computing devices 12-16 may each be a portablecomputing device and/or a fixed computing device. A portable computingdevice may be a social networking device, a gaming device, a cell phone,a smart phone, a digital assistant, a digital music player, a digitalvideo player, a laptop computer, a handheld computer, a tablet, a videogame controller, and/or any other portable device that includes acomputing core. A fixed computing device may be a computer (PC), acomputer server, a cable set-top box, a satellite receiver, a televisionset, a printer, a fax machine, home entertainment equipment, a videogame console, and/or any type of home or office computing equipment.Note that each of the managing unit 18 and the integrity processing unit20 may be separate computing devices, may be a common computing device,and/or may be integrated into one or more of the computing devices 12-16and/or into one or more of the storage units 36.

Each interface 30, 32, and 33 includes software and hardware to supportone or more communication links via the network 24 indirectly and/ordirectly. For example, interface 30 supports a communication link (e.g.,wired, wireless, direct, via a LAN, via the network 24, etc.) betweencomputing devices 14 and 16. As another example, interface 32 supportscommunication links (e.g., a wired connection, a wireless connection, aLAN connection, and/or any other type of connection to/from the network24) between computing devices 12 and 16 and the DSN memory 22. As yetanother example, interface 33 supports a communication link for each ofthe managing unit 18 and the integrity processing unit 20 to the network24.

Computing devices 12 and 16 include a dispersed storage (DS) clientmodule 34, which enables the computing device to dispersed storage errorencode and decode data (e.g., data 40) as subsequently described withreference to one or more of FIGS. 3-8. In this example embodiment,computing device 16 functions as a dispersed storage processing agentfor computing device 14. In this role, computing device 16 dispersedstorage error encodes and decodes data on behalf of computing device 14.With the use of dispersed storage error encoding and decoding, the DSN10 is tolerant of a significant number of storage unit failures (thenumber of failures is based on parameters of the dispersed storage errorencoding function) without loss of data and without the need for aredundant or backup copies of the data. Further, the DSN 10 stores datafor an indefinite period of time without data loss and in a securemanner (e.g., the system is very resistant to unauthorized attempts ataccessing the data).

In operation, the managing unit 18 performs DS management services. Forexample, the managing unit 18 establishes distributed data storageparameters (e.g., vault creation, distributed storage parameters,security parameters, billing information, user profile information,etc.) for computing devices 12-14 individually or as part of a group ofuser devices. As a specific example, the managing unit 18 coordinatescreation of a vault (e.g., a virtual memory block associated with aportion of an overall namespace of the DSN) within the DSN memory 22 fora user device, a group of devices, or for public access and establishesper vault dispersed storage (DS) error encoding parameters for a vault.The managing unit 18 facilitates storage of DS error encoding parametersfor each vault by updating registry information of the DSN 10, where theregistry information may be stored in the DSN memory 22, a computingdevice 12-16, the managing unit 18, and/or the integrity processing unit20.

The managing unit 18 creates and stores user profile information (e.g.,an access control list (ACL)) in local memory and/or within memory ofthe DSN memory 22. The user profile information includes authenticationinformation, permissions, and/or the security parameters. The securityparameters may include encryption/decryption scheme, one or moreencryption keys, key generation scheme, and/or data encoding/decodingscheme.

The managing unit 18 creates billing information for a particular user,a user group, a vault access, public vault access, etc. For instance,the managing unit 18 tracks the number of times a user accesses anon-public vault and/or public vaults, which can be used to generate aper-access billing information. In another instance, the managing unit18 tracks the amount of data stored and/or retrieved by a user deviceand/or a user group, which can be used to generate a per-data-amountbilling information.

As another example, the managing unit 18 performs network operations,network administration, and/or network maintenance. Network operationsincludes authenticating user data allocation requests (e.g., read and/orwrite requests), managing creation of vaults, establishingauthentication credentials for user devices, adding/deleting components(e.g., user devices, storage units, and/or computing devices with a DSclient module 34) to/from the DSN 10, and/or establishing authenticationcredentials for the storage units 36. Network administration includesmonitoring devices and/or units for failures, maintaining vaultinformation, determining device and/or unit activation status,determining device and/or unit loading, and/or determining any othersystem level operation that affects the performance level of the DSN 10.Network maintenance includes facilitating replacing, upgrading,repairing, and/or expanding a device and/or unit of the DSN 10.

The integrity processing unit 20 performs rebuilding of ‘bad’ or missingencoded data slices. At a high level, the integrity processing unit 20performs rebuilding by periodically attempting to retrieve/list encodeddata slices, and/or slice names of the encoded data slices, from the DSNmemory 22. For retrieved encoded slices, they are checked for errors dueto data corruption, outdated version, etc. If a slice includes an error,it is flagged as a ‘bad’ slice. For encoded data slices that were notreceived and/or not listed, they are flagged as missing slices. Badand/or missing slices are subsequently rebuilt using other retrievedencoded data slices that are deemed to be good slices to produce rebuiltslices. The rebuilt slices are stored in the DSN memory 22.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (IO)controller 56, a peripheral component interconnect (PCI) interface 58,an IO interface module 60, at least one IO device interface module 62, aread only memory (ROM) basic input output system (BIOS) 64, and one ormore memory interface modules. The one or more memory interfacemodule(s) includes one or more of a universal serial bus (USB) interfacemodule 66, a host bus adapter (HBA) interface module 68, a networkinterface module 70, a flash interface module 72, a hard drive interfacemodule 74, and a DSN interface module 76.

The DSN interface module 76 functions to mimic a conventional operatingsystem (OS) file system interface (e.g., network file system (NFS),flash file system (FFS), disk file system (DFS), file transfer protocol(FTP), web-based distributed authoring and versioning (WebDAV), etc.)and/or a block memory interface (e.g., small computer system interface(SCSI), interne small computer system interface (iSCSI), etc.). The DSNinterface module 76 and/or the network interface module 70 may functionas one or more of the interface 30-33 of FIG. 1. Note that the IO deviceinterface module 62 and/or the memory interface modules 66-76 may becollectively or individually referred to as IO ports.

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data. When a computing device 12 or 16 has data tostore it disperse storage error encodes the data in accordance with adispersed storage error encoding process based on dispersed storageerror encoding parameters. The dispersed storage error encodingparameters include an encoding function (e.g., information dispersalalgorithm, Reed-Solomon, Cauchy Reed-Solomon, systematic encoding,non-systematic encoding, on-line codes, etc.), a data segmentingprotocol (e.g., data segment size, fixed, variable, etc.), and per datasegment encoding values. The per data segment encoding values include atotal, or pillar width, number (T) of encoded data slices per encodingof a data segment (i.e., in a set of encoded data slices); a decodethreshold number (D) of encoded data slices of a set of encoded dataslices that are needed to recover the data segment; a read thresholdnumber (R) of encoded data slices to indicate a number of encoded dataslices per set to be read from storage for decoding of the data segment;and/or a write threshold number (W) to indicate a number of encoded dataslices per set that must be accurately stored before the encoded datasegment is deemed to have been properly stored. The dispersed storageerror encoding parameters may further include slicing information (e.g.,the number of encoded data slices that will be created for each datasegment) and/or slice security information (e.g., per encoded data sliceencryption, compression, integrity checksum, etc.).

In the present example, Cauchy Reed-Solomon has been selected as theencoding function (a generic example is shown in FIG. 4 and a specificexample is shown in FIG. 5); the data segmenting protocol is to dividethe data object into fixed sized data segments; and the per data segmentencoding values include: a pillar width of 5, a decode threshold of 3, aread threshold of 4, and a write threshold of 4. In accordance with thedata segmenting protocol, the computing device 12 or 16 divides the data(e.g., a file (e.g., text, video, audio, etc.), a data object, or otherdata arrangement) into a plurality of fixed sized data segments (e.g., 1through Y of a fixed size in range of Kilo-bytes to Tera-bytes or more).The number of data segments created is dependent of the size of the dataand the data segmenting protocol.

The computing device 12 or 16 then disperse storage error encodes a datasegment using the selected encoding function (e.g., Cauchy Reed-Solomon)to produce a set of encoded data slices. FIG. 4 illustrates a genericCauchy Reed-Solomon encoding function, which includes an encoding matrix(EM), a data matrix (DM), and a coded matrix (CM). The size of theencoding matrix (EM) is dependent on the pillar width number (T) and thedecode threshold number (D) of selected per data segment encodingvalues. To produce the data matrix (DM), the data segment is dividedinto a plurality of data blocks and the data blocks are arranged into Dnumber of rows with Z data blocks per row. Note that Z is a function ofthe number of data blocks created from the data segment and the decodethreshold number (D). The coded matrix is produced by matrix multiplyingthe data matrix by the encoding matrix.

FIG. 5 illustrates a specific example of Cauchy Reed-Solomon encodingwith a pillar number (T) of five and decode threshold number of three.In this example, a first data segment is divided into twelve data blocks(D1-D12). The coded matrix includes five rows of coded data blocks,where the first row of X11-X14 corresponds to a first encoded data slice(EDS 1_1), the second row of X21-X24 corresponds to a second encodeddata slice (EDS 2_1), the third row of X31-X34 corresponds to a thirdencoded data slice (EDS 3_1), the fourth row of X41-X44 corresponds to afourth encoded data slice (EDS 4_1), and the fifth row of X51-X54corresponds to a fifth encoded data slice (EDS 5_1). Note that thesecond number of the EDS designation corresponds to the data segmentnumber.

Returning to the discussion of FIG. 3, the computing device also createsa slice name (SN) for each encoded data slice (EDS) in the set ofencoded data slices. A typical format for a slice name 80 is shown inFIG. 6. As shown, the slice name (SN) 80 includes a pillar number of theencoded data slice (e.g., one of 1-T), a data segment number (e.g., oneof 1-Y), a vault identifier (ID), a data object identifier (ID), and mayfurther include revision level information of the encoded data slices.The slice name functions as, at least part of, a DSN address for theencoded data slice for storage and retrieval from the DSN memory 22.

As a result of encoding, the computing device 12 or 16 produces aplurality of sets of encoded data slices, which are provided with theirrespective slice names to the storage units for storage. As shown, thefirst set of encoded data slices includes EDS 1_1 through EDS 5_1 andthe first set of slice names includes SN 1_1 through SN 5_1 and the lastset of encoded data slices includes EDS 1_Y through EDS 5_Y and the lastset of slice names includes SN 1_Y through SN 5_Y.

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of a data object that was dispersed storage error encodedand stored in the example of FIG. 4. In this example, the computingdevice 12 or 16 retrieves from the storage units at least the decodethreshold number of encoded data slices per data segment. As a specificexample, the computing device retrieves a read threshold number ofencoded data slices.

To recover a data segment from a decode threshold number of encoded dataslices, the computing device uses a decoding function as shown in FIG.8. As shown, the decoding function is essentially an inverse of theencoding function of FIG. 4. The coded matrix includes a decodethreshold number of rows (e.g., three in this example) and the decodingmatrix in an inversion of the encoding matrix that includes thecorresponding rows of the coded matrix. For example, if the coded matrixincludes rows 1, 2, and 4, the encoding matrix is reduced to rows 1, 2,and 4, and then inverted to produce the decoding matrix.

FIG. 9 is a diagram of an example of the distributed computing systemperforming a distributed storage and task processing operation. Thedistributed computing system includes a DS (distributed storage and/ortask) client module 34 (which may be in user device 14 and/or in DSprocessing unit 16 of FIG. 1), a network 24, a plurality of DS executionunits 1-n that includes two or more DS execution units 36 of FIG. 1(which form at least a portion of DSTN module 22 of FIG. 1), a DSmanaging module (not shown), and a DS integrity verification module (notshown). The DS client module 34 includes an outbound DS processingsection 104 and an inbound DS processing section 106. Each of the DSexecution units 1-n includes a controller 110, a processing module 108,memory 112, a DT (distributed task) execution module 90, and a DS clientmodule 34.

In an example of operation, the DS client module 34 receives data 92 andone or more tasks 94 to be performed upon the data 92. The data 92 maybe of any size and of any content, where, due to the size (e.g., greaterthan a few Terra-Bytes), the content (e.g., secure data, etc.), and/ortask(s) (e.g., MIPS intensive), distributed processing of the task(s) onthe data is desired. For example, the data 92 may be one or more digitalbooks, a copy of a company's emails, a large-scale Internet search, avideo security file, one or more entertainment video files (e.g.,television programs, movies, etc.), data files, and/or any other largeamount of data (e.g., greater than a few Terra-Bytes).

Within the DS client module 34, the outbound DS processing section 104receives the data 92 and the task(s) 94. The outbound DS processingsection 104 processes the data 92 to produce slice groupings 96. As anexample of such processing, the outbound DS processing section 104partitions the data 92 into a plurality of data partitions. For eachdata partition, the outbound DS processing section 104 dispersed storage(DS) error encodes the data partition to produce encoded data slices andgroups the encoded data slices into a slice grouping 96. In addition,the outbound DS processing section 104 partitions the task 94 intopartial tasks 98, where the number of partial tasks 98 may correspond tothe number of slice groupings 96.

The outbound DS processing section 104 then sends, via the network 24,the slice groupings 96 and the partial tasks 98 to the DS executionunits 1-n of the DSTN module 22 of FIG. 1. For example, the outbound DSprocessing section 104 sends slice group 1 and partial task 1 to DSexecution unit 1. As another example, the outbound DS processing section104 sends slice group #n and partial task #n to DS execution unit #n.

Each DS execution unit performs its partial task 98 upon its slice group96 to produce partial results 102. For example, DS execution unit #1performs partial task #1 on slice group #1 to produce a partial result#1, for results. As a more specific example, slice group #1 correspondsto a data partition of a series of digital books and the partial task #1corresponds to searching for specific phrases, recording where thephrase is found, and establishing a phrase count. In this more specificexample, the partial result #1 includes information as to where thephrase was found and includes the phrase count.

Upon completion of generating their respective partial results 102, theDS execution units send, via the network 24, their partial results 102to the inbound DS processing section 106 of the DS client module 34. Theinbound DS processing section 106 processes the received partial results102 to produce a result 104. Continuing with the specific example of thepreceding paragraph, the inbound DS processing section 106 combines thephrase count from each of the DS execution units 36 to produce a totalphrase count. In addition, the inbound DS processing section 106combines the ‘where the phrase was found’ information from each of theDS execution units 36 within their respective data partitions to produce‘where the phrase was found’ information for the series of digitalbooks.

In another example of operation, the DS client module 34 requestsretrieval of stored data within the memory of the DS execution units 36(e.g., memory of the DSTN module). In this example, the task 94 isretrieve data stored in the memory of the DSTN module. Accordingly, theoutbound DS processing section 104 converts the task 94 into a pluralityof partial tasks 98 and sends the partial tasks 98 to the respective DSexecution units 1-n.

In response to the partial task 98 of retrieving stored data, a DSexecution unit 36 identifies the corresponding encoded data slices 100and retrieves them. For example, DS execution unit #1 receives partialtask #1 and retrieves, in response thereto, retrieved slices #1. The DSexecution units 36 send their respective retrieved slices 100 to theinbound DS processing section 106 via the network 24.

The inbound DS processing section 104 converts the retrieved slices 100into data 92. For example, the inbound DS processing section 106de-groups the retrieved slices 100 to produce encoded slices per datapartition. The inbound DS processing section 104 then DS error decodesthe encoded slices per data partition to produce data partitions. Theinbound DS processing section 104 de-partitions the data partitions torecapture the data 92.

FIG. 10A is a diagram of an embodiment of a structure of a large dataobject 350 where the large data object 350 is divided into data regions1-N. The large data object 350 includes at least one of a multimediafile, a video file, an audio file, a text file, an image file, a drawingfile, etc. The large data object 350 may include as many as 100 MB ormore. A data object storage tracking table 352 is created with regardsto storage of the large data object 350 and a dispersed storage network.The data object storage tracking table 352 includes an availableregion(s) field 354, a region(s) in or awaiting write process and notavailable field 356, and a region(s) in delete process and not availablefield 358.

The fields of the data object storage tracking table 352 are utilized totrack status of storage of the data regions of the large data object350. For example, the available region(s) field 354 includes data regionidentifiers associated with data regions that are available forretrieval. As another example, the region(s) in or awaiting writeprocess and not available field 356 includes other data regionidentifiers associated with other data regions that are unavailable forretrieval when associated with an open write transaction. Such an openwrite transaction is associated with a multi-step writing process (e.g.,issuing write slice requests, receiving write slice responses, issuingcommit transaction requests) to store the other data regions. As yetanother example, the region(s) in delete process and not available field358 includes still other data region identifiers associated with stillother data regions that are unavailable for retrieval when associatedwith an open delete transaction (e.g., issuing delete slice requests,receiving delete slice responses, issuing commit transaction requests).

A mapping of the data regions may be generated for the very large dataobject and the mapping may be stored in at least one of a local memoryof an associated computing device and as a set of encoded mapping slicesin storage units of the dispersed storage network. Subsequent to storageof the large data object in the dispersed storage network, the verylarge data object may be edited by one of revising one or more of thedata regions and deleting one or more of the data regions. The dataobject storage tracking table 352 may be updated when the very largedata object is edited.

FIG. 10B is a diagram of an embodiment of a structure of a data objectstorage tracking table 352 that includes an available region(s) field354, a region(s) in or awaiting write process and not available field356, and a region(s) in delete process and not available field 358. Thedata object storage tracking table 352 is associated with a very largedata object that is stored as a plurality of sets of encoded data slicesin a dispersed storage network (DSN). The data object storage trackingtable 352 may be utilized to identify storage locations of the verylarge data object within the DSN. The very large data object may bestored as a plurality of data regions within the DSN where each dataregion includes a plurality of data segments. Each data segment of theplurality of data segments is encoded using a dispersed storage errorcoding function to produce a set of encoded data slices of the pluralityof sets of encoded data slices. For example, a first grouping of sets ofencoded data slices is produced corresponding to a first data region anda second grouping of sets of encoded data slices is producedcorresponding to a second data region. Each region of the one or moreregions is stored in the DSN at a storage location corresponding to adispersed storage (DS) address for the region. Each region may beuniquely identified by a region identifier (ID). The data object storagetracking table 352 may be stored in the DSN as a set of table slices ata storage location that includes a table DS address. At least one of adirectory and an index may be utilized to identify the table DS addressbased on an object name (e.g., data ID) for the very large data object.

The available regions field 354 identifies visible regions, if any, byone or more region entries. A data region is visible when each datasegment associated with the data region includes at least a writethreshold number of favorably committed encoded data slices stored inthe DSN. A favorably committed encoded data slice is visible forretrieving from a storage unit of the DSN when the encoded data slicehas been written to the DSN and is associated with an executed committransaction request.

Each region entry includes a region ID field (e.g., region 1), a DSaddress field (e.g., F530), a region size field (e.g., 100M), and asegment size field (e.g., 10M). A region ID entry is included in theregion ID field to uniquely identify the region. A DS address entry isincluded in the DS address field to identify a storage location withinthe DSN of a first data segment of the plurality of data segmentsassociated with the region. For example, the DS address entry identifiesa source name (e.g., F530) for a first data segment. Source namescorresponding to other data segments of the one or more data segments ofthe region may be generated based on the source name for the first datasegment (e.g., incrementing a segment field entry by one for eachsequential data segment of the plurality of data segments of theregion). A region size entry of the region size field indicates a sizeof the region (e.g., 100M bytes). A segment size entry of the segmentsize field indicates a size (e.g., 10M bytes) of each data segment ofthe plurality of data segments of the region. A number of data segmentsmay be determined by dividing the region size entry by the segment sizeentry.

The regions in or awaiting write process and not available field 356identifies open write transactions with regards to the very large dataobject. An open write transaction includes a write transaction that isin progress for a data region but has not yet produced visibility of thedata region. The regions in or awaiting write process and not availablefield 356 includes a subsection for each, if any, transaction that isassociated with at least one data region of an open write transaction.Each subsection of the open write transaction section includes atransaction identifier (e.g., 3000) and a region entry for each dataregion associated with the open write transaction (e.g., region 30, DSaddress 4750, region size 500M, and segment size 100M).

The regions in delete process and not available field 358 identifiesopen delete transactions with regards to the very large data object. Anopen delete transaction includes a delete transaction that is inprogress for a data region but has not yet produced full deletion of thedata region. The regions in delete process and not available field 358includes a subsection for each, if any, transaction that is associatedwith at least one data region of an open delete transaction. Eachsubsection includes a transaction identifier (ID) and a region entry foreach data region associated with the open delete transaction (e.g.,region 15, DS address D990, region size 1 G, and segment size 100M).

FIG. 10C, and 10F-10J are schematic block diagrams of an embodiment of adispersed storage network (DSN) that illustrate steps of an example ofstoring data in a dispersed storage network (DSN). The DSN includesdistributed storage (DS) client modules 1 and 2 and the network 24 ofFIG. 1, and a set of dispersed storage (DS) units 1-n. Each DS unit maybe storage unit 36 of FIG. 1. Each DS client module includes theoutbound DS processing 104 and the inbound DS processing 106 of FIG. 9.Each DS unit includes the processing module 108 and the memory 112 ofFIG. 3.

In the example of storing data, as illustrated in FIG. 10C, the outboundDS processing 104 of a DS client module 1 receives a write requestregarding a very large data object A. The outbound DS processing 104determines whether the write request is an initial write request for thevery large data object or a write request for editing the very largedata object. As a specific example, the outbound DS processing 104retrieves an indication from the write request. As another specificexample, the outbound DS processing 104 searches for a data objectstorage tracking table A (e.g., associated with the very large dataobject A) and, when it is not found, indicates that the write request isthe initial write request. The searching includes at least one ofaccessing a local memory of the DS client module 1 and accessing adirectory using an identifier of the very large data object A todetermine whether a DS address exists for the data object storagetracking table A.

When the write request is the initial write request, the outbound DSprocessing 104 divides the very large data object A into a plurality ofdata regions. The data regions may be of a common size or of differentsizes. The outbound DS processing 104 generates the data object storagetracking table A to include an empty available regions field 354 and anempty regions in or awaiting write process and not available field foropen transaction 1, where at least one data region is to be writtenutilizing transaction 1. Alternatively, or in addition to, the outboundDS processing 104 generates one or more other transactions for storingother data regions. For example, FIG. 10D illustrates an example ofwriting data regions where a first data region is written with a firsttransaction, second and third data regions are written with a secondtransaction, a first sub portion of a fourth data region is written witha third transaction, and a second sub portion of the fourth data regionis written with a fourth transaction.

Returning to FIG. 10C, having generated the data object storage trackingtable A, the outbound DS processing 104 dispersed storage error encodesthe data object storage tracking table A to produce a set of encodedtable slices A_1 through A_n. The outbound DS processing 104 issues, viathe network 24, write table slice requests 360 to the set of DS units1-n as write table slice requests 1-n to write the set of encoded tableslices to the DS units 1-n. For example, the processing module 108 of DSunit 2 receives write table slice request 2 and stores the encoded tableslice A_2 in the memory 112 of DS unit 2.

FIG. 10D is a diagram of an example of writing data regions. In anexample of operation, transaction number 2 is generated for writing dataregions 2 and 3 to dispersed storage (DS) storage units. Data region 2is divided into data segments of data region 2 which are dispersestorage error encoded to produce first sets of encoded data slices. Dataregion 3 is divided into data segments of data region 3 which aredisperse storage error encoded to produce second sets of encoded dataslices. DSN write requests are sent, which include the transactionnumber 2, regarding storing the first and second sets of encoded dataslices to the DS units. When at least a write threshold number of writeresponses is received for each of the first and second sets of encodeddata slices, a data object storage tracking table A is updated toindicate that the first and second data regions are available. Forexample, entries of data regions 1 and 2 are included in an availableregions field of the data object storage tracking table A.

FIG. 10E is a diagram of an example of writing a data region 1 to a setof storage units 1-n of a dispersed storage network (DSN). The dataregion 1 is associated with a transaction 1 and is divided into aplurality of data segments 1-x. The plurality of data segments 1-x areeach disperse storage error encoded to produce a plurality of sets ofencoded data slices 1-1 through 1-n, 2-1 through 2-n, etc. through x-1through x-n. Dispersed storage network (DSN) write requests regardingstoring the plurality of sets of encoded data slices are sent to thestorage units 1-n. Prior to storage of all of the encoded data slices,the data region 1 is associated with an open write phase for transaction1 such that data region 1 is not available for retrieval. When at leasta write threshold number of write responses is received from the set ofstorage units 1-n for each of the plurality of sets of encoded dataslices, a data object storage tracking table A is updated to indicatethat the first data region is available for retrieval.

FIG. 10F illustrates a continuation of the example of storing data. Whenthe first and second data regions are to be associated with first andsecond transactions, for the first data region, the outbound DSprocessing 104 divides the first data region into data segments anddisperse storage error encodes the data segments to produce sets ofencoded data slices. The outbound DS processing 104 sends write slicerequests 362 that includes write slice requests 1-n as DSN writerequests regarding storing the sets of encoded data slices to the set ofDS units 1-n. For example, DS unit 1 stores data slice A_1_1_1 for dataobject A, region 1, segment 1, and slice pillar index 1 and stores dataslice A_1_2_1 for segment 2 etc.

The outbound DS processing 104 updates the data object storage trackingtable A to indicate that data region 1 is not available and that dataregion 1 is associated with open write transaction 1. As a specificexample, the inbound DS processing 106 of DS client module 1 retrievesat least a decode threshold number of encoded table slices of the set ofencoded table slices A_1 through A_n and decodes the at least a decodethreshold number of encoded table slices to recapture the data objectstorage tracking table A. The outbound DS processing 104 updates thedata object storage tracking table A to produce an updated data objectstorage tracking table A (e.g., associating data region 1 with openwrite transaction 1). Having produced the updated data object storagetracking table A, the outbound DS processing 104 disperse storage errorencodes the updated data object storage tracking table to produce a setof updated encoded table slices A_1 through A_n and writes the set ofupdated encoded table slices to the set of DS units 1-n.

FIG. 10G illustrates a continuation of the example of storing data. Whenat least a write threshold number of write slice responses 364 (e.g.,write slice responses 1-n) is received for each of the sets of encodeddata slices, the outbound DS processing 104 updates the data objectstorage tracking table A to indicate that the first data region isavailable for retrieval (e.g., associating data region 1 with thevisible regions 354. The outbound DS processing 104 further updates thedata object storing tracking table A to indicate that transaction 2 isan open write transaction, where transaction 2 is associated with dataregion 2. The outbound DS processing 104 encodes the updated data objectstoring tracking table A to produce updated encoded table slices A_1through A_n. The outbound DS processing 104 issues write table slicerequests 360 which includes write table slice requests 1-n to the set ofDS units 1-n. Each DS unit stores a corresponding encoded table slice ina corresponding memory 112.

FIG. 10H illustrates a continuation of the example of storing data wherea very large data object A request is received by the DS client module 2when storing all of the data regions of the very large data object A hasnot been completed (e.g., only data region 1 is visible). The inbound DSprocessing 106 of DS client module 2 performs at least one of adirectory lookup and an index lookup to identify the DS address of thedata object storage tracking table A based on the identifier of the verylarge data object A. The inbound DS processing 106 issues read slicerequests 366 to the set of DS units 1-n, where the read slice requests366 includes read slice requests 1-n based on the DS address of the dataobject storage tracking table A. The inbound DS processing 106 receivesread slice responses 368 (e.g., read slice responses 1-n) from the setof DS units 1-n. The inbound DS processing 106 disperse storage errordecodes at least a decode threshold number of encoded table slices fromthe read slice responses 368 to reproduce the data object storagetracking table A.

Having recovered the data object storage tracking table A, the inboundDS processing 106 identifies one or more visible regions (e.g., dataregion 1) from the data object storage tracking table A. The inbound DSprocessing 106 identifies DS addresses associated with one or more datasegments of data region 1 and issues further read slice requests 366based on the DS addresses. The inbound DS processing 106 receives readslice responses 368 that includes one or more sets of encoded dataslices (e.g., data slice A_1_1_1 through A_1_1_n for data segment 1,etc.). The inbound DS processing 106 disperse storage error decodes theone or more sets of encoded data slices to reproduce data region 1.Alternatively, or in addition to, the inbound DS processing 106identifies the open write transaction 2 from the data object storagetracking table A and determines to subsequently recover another dataregion (e.g., data region 2) when the open write transaction 2 hascompleted.

FIG. 101 illustrates a continuation of the example of storing data. Theoutbound DS processing 104 of a DS client module 1 divides data region 2into data segments of the second data region. The outbound DS processing104 disperse storage error encodes the data segments of the second dataregion to produce second sets of encoded data slices (e.g., data slicesA_2_1_1 through A_2_1_n for a first data segment of the second dataregion). The outbound DS processing 104 sends write slice requests 362(e.g., DSN write requests) regarding storing the second sets of encodeddata slices to the set of DS units 1-n. The outbound DS processing 104updates the data object storage tracking table A to associate dataregion 2 with the open write transaction 2. The outbound DS processing104 may store the updated data object storage tracking table A in theset of DS units 1-n (e.g., as an updated set of encoded table slices).

FIG. 10J illustrates a continuation of the example of storing data. Whenthe outbound DS processing 104 of a DS client module 1 receives at leasta write threshold number of write slice responses 364 (e.g., secondwrite responses) for each of the second sets of encoded data slices, theoutbound DS processing module 104 updates the data object storagetracking table A to indicate that the second data region is available byassociating the identifier for data region 2 with the visible regionsfield 354 such that both data regions 1 and 2 are indicated as visibleregions. The outbound DS processing 104 further updates the data objectstoring tracking table A to exclude open write transactions when thestoring of the very large data object A has been completed. The outboundDS processing 104 dispersed storage error encodes the updated dataobject storage tracking table A to produce an updated set of encodedtable slices A_1 through A_n and issues write table slice requests 360to the set of DS units 1-n, where the write table slice requests 360includes the updated set of encoded data slices.

When the write request is for editing the very large data object A, theoutbound DS processing 104 identifies one data region as being editedbased on the write request. The outbound DS processing 104 updates thedata object storage tracking table A to indicate that the one dataregion is unavailable (e.g., an open write transaction, an open deletetransaction). The outbound DS processing 104 disperse storage errorencodes one or more edited data segments of a plurality of data segmentsof the one data region to produce one or more sets of edited encodeddata slices. The outbound DS processing 104 sends updated DSN writerequests 362 regarding storing the one or more sets of edited encodeddata slices to the set of DS units 1-n. When at least a write thresholdnumber of write responses 364 is received for each of the one or moresets of edited encoded data slices, the outbound DS processing 104updates the data object storage tracking table A to indicate that theone data region is available.

FIG. 11 is a flowchart illustrating an example of writing a data object.The method begins at step 390 where a processing module (e.g., of adispersed storage processing module of a computing device of a dispersedstorage network (DSN)) receives a write request regarding a very largedata object. The method continues at step 392 where the processingmodule determines whether the write request is an initial write requestfor the very large data object or a write request for editing the verylarge data object. As examples of editing the very large data object,the editing may include revising one or more data regions of the verylarge data object or deleting the one or more of the data regions. As aspecific example, the processing module retrieves an indication from thewrite request (e.g., a flag denoting a new write request). As anotherspecific example, the processing module searches for a data objectstorage tracking table associated with the very large data object and,when it is not found, indicates that the write request is the initialwrite request. The method branches to step 404 when the write request isthe initial write request. The method continues to step 394 when thewrite request is the write request for editing.

When the write request is for editing the very large data object, themethod continues at step 394 where the processing module identifies oneof the data regions being edited based on the write request (e.g., anoffset identifier, a region identifier). The method continues at step396 where the processing module updates the data object storage trackingtable to indicate that the one data region is unavailable. As a specificexample, the processing module retrieves at least a decode thresholdnumber of encoded table slices of a set of encoded table slices fromstorage units of the DSN. Having retrieved the slices, the processingmodule decodes the at least a decode threshold number of encoded tableslices to recapture the data object storage tracking table. Next, theprocessing module updates the data object storage tracking table toproduce an updated data object storage tracking table (e.g., indicatingthat the one data region is unavailable). Having updated the data objectstorage tracking table, the processing module dispersed storage errorencodes the updated data object storage tracking table to produce a setof updated encoded table slices. Next, the processing module writes theset of updated encoded table slices to the at least some of the storageunits for storage therein.

The method continues at step 398 where the processing module dispersestorage error encodes one or more edited data segments of data segmentsof the one data region to produce one or more sets of edited encodeddata slices. The method continues at step 400 where the processingmodule sends updated DSN write requests regarding storing the one ormore sets of edited encoded data slices to the storage units. When atleast a write threshold number of write responses is received for eachof the one or more sets of edited encoded data slices, the methodcontinues at step 402 where the processing module updates the dataobject storage tracking table to indicate that the one data region isavailable.

When the write request is the initial write request, the methodcontinues at step 404 where the processing module divides the very largedata object into data regions. The method continues at step 406 wherethe processing module generates the data object storage tracking tablethat includes a section for identifying, if any, one or more dataregions of the data regions that are available for retrieval and asection for identifying, if any, one or more other data regions that areunavailable for retrieval. The processing module disperse storage errorencodes the data object storage tracking table to produce the set ofencoded table slices and writes the set of encoded table slices to atleast some of the storage units.

For a first data region, the method continues at step 408 where theprocessing module divides the first data region into data segments. Themethod continues at step 410 where the processing module generates amapping of the data regions for the very large data object and storesthe mapping in at least one of a local memory of the computing deviceand as a set of encoded mapping slices in at least some of the storageunits. The method continues at step 412 where the processing moduledispersed storage error encodes the data segments to produce sets ofencoded data slices. The method continues at step 414 where theprocessing module sends DSN write requests regarding storing the sets ofencoded data slices to the storage units of the DSN. When at least awrite threshold number of write responses is received for each of thesets of encoded data slices, the method continues at step 416 where theprocessing module updates updating the data object storage trackingtable to indicate that the first data region is available for retrieval.

Alternatively, or in addition to, the method continues at step 418 wherethe processing module stores a second data region. As a specificexample, the processing module divides the second data region into datasegments of the second data region and disperse storage error encodesthe data segments of the second data region to produce second sets ofencoded data slices. Next, the processing module sends second DSN writerequests regarding storing the second sets of encoded data slices to thestorage units. When at least a write threshold number of second writeresponses are received for each of the second sets of encoded dataslices, the processing module updates the data object storage trackingtable to indicate that the second data region is available.

Alternatively, the processing module writes one or more data regions aspart of a common transaction. As a specific example, the processingmodule generates a transaction number for writing the one or more dataregions to the storage units. When the transaction number includes atleast two data regions, for a first one of the at least two dataregions, the processing module divides the first one of the at least twodata regions into data segments of the first one of the at least twodata regions and disperse storage error encodes the data segments of thefirst one of the at least two data regions to produce first sets ofencoded data slices. For a second one of the at least two data regions,the processing module divides the second one of the at least two dataregions into data segments of the second one of the at least two dataregions and disperse storage error encodes the data segments of thesecond one of the at least two data regions to produce second sets ofencoded data slices. Next, the processing module sends DSN writerequests, which include the transaction number, regarding storing thefirst and second sets of encoded data slices to the storage units. Whenat least a write threshold number of write responses is received foreach of the first and second sets of encoded data slices, the processingmodule updates the data object storage tracking table to indicate thatthe first one and the second one of the at least two data regions areavailable.

FIG. 12 is a flowchart illustrating an example of overwriting a dataobject, which includes similar steps to FIGS. 41 and 43. The methodbegins at step 436 where a processing module (e.g., of a dispersedstorage (DS) processing module of a computing device of a dispersedstorage network (DSN)) receives a write data object request (e.g., anoverwrite operation request) that includes at least a portion of a verylarge data object for storage and an object identifier associated with astored very large data object stored in a dispersed storage network(DSN) memory. The method continues with steps 372 and 376 of FIG. 41where the processing module identifies a DS address associated with theobject identifier and retrieves a region header object from the DSNmemory using the DS address.

The method continues at step 438 where the processing module updates theregion header object to include a new open write transaction with noregions entries. For example, the processing module generates atransaction ID associated with the write request and generates an openwrite transaction section to include the transaction ID. The methodcontinues at step 440 where the processing module stores the updatedregion header object in the DSN memory. For example, the processingmodule encodes the updated region header object using a dispersedstorage error coding function to produce a set of header slices,generates and outputs a set of write slice requests that includes thetransaction ID, the set of header slices, and a set of header slicenames based on the DS address of the region header object, and generatesand outputs a set of commit write requests that includes the transactionID when a write threshold number of favorable write slice responses hasbeen received from the DSN memory.

The method continues at step 442 where the processing module stores afirst region of the data object in the DSN memory. The method continuesat step 444 where the processing module updates the region header objectin the DSN memory. The method continues at step 446 where the processingmodule stores any subsequent regions of the data object in the DSNmemory. The method continues at step 448 where the processing moduleupdates the region header object in the DSN memory for subsequentregions.

When each segment of each region has been committed, the methodcontinues at step 450 where the processing module updates the regionheader object to include an open delete transaction. The updatingincludes generating a second transaction ID to be associated with adelete operation of the previously stored data. The method continueswith step 424 of FIG. 43 where the processing module updates the regionheader object by transferring region entries of visible regions to theopen delete transaction section.

The method continues at step 452 where the processing module updates theregion header object by transferring region entries of the new openwrite transaction section to the visible regions section. Suchtransferring establishes the received data object as the currentrevision of the data object. The method continues at step 454 where theprocessing module stores the updated region header object in the DSNmemory such that subsequent read operations access the received dataobject. The method continues with steps 428 and 430 of FIG. 43 where,for each region associated with the open delete transaction, theprocessing module facilitates deleting the region from the DSN memoryand for each deleted region, the processing module updates the regionheader object in the DSN memory to disassociate the region with the opendelete transaction.

FIG. 13 is a flowchart illustrating an example of updating a data objectwhen competing devices are attempting to write to the same DS units. Inthis instance the write data request is broken into two or more phases.As shown in step 504, instead of initiating write requests, one or moreDS processing modules transmit lock requests to the DS units holdingencoded data slices for the data object. Lock requests can include slicenames and a transaction identifier associated with the data object beingupdated. Alternatively, DS processing units can send multiple lockmessages for a single transaction identifier, followed by a singlepersist message being transmitted for all of the affected DS units. Lockrequests can include additional information to assist in the updatingprocess, including information that can be used by a DS units toidentify every DS unit involved in the update. The information couldinclude a list of names, naming schemes and other information that willbe known by one skilled in the relevant art.

Based on whether the particular encoded data slices are already beingoverwritten by another DS processing unit the DS units either grant thelock request, ignore the lock requests or actively reject the lockrequests. The decision to grant a lock request can depend on whetheranother processing unit has already been granted a lock request forencoded data slices with the same slice name. The DS units may alsorespond to the one or more processing units indicating that another lockrequest has already been granted.

The method continues at step 506, where the one or more DS processingmodules receive responses from the DS units and the one or more DSprocessing modules determine (at step 510) whether a write thresholdnumber of distributed storage units have granted the requested lockrequests. When a write threshold number of DS units have granted lockrequests, the one or more DS processing modules transmit a persistmessage to each of the write threshold number of distributed storageunits, as shown in step 512. A persist message can include the encodeddata slices that the one or more processing units intend to update,along with other information to assist the DS units. On receipt of thepersist message the DS units unlock the slice names associated with thetransaction identifier and the DS units deny subsequent lock requestsfrom other DS processing units until the encoded data slices have beensuccessfully overwritten.

When a write threshold number of distributed storage units fail to grantlock requests the method continues at step 522, and the one or more DSprocessing units can transmit a rollback message to any of the DS unitsfrom which the lock request has been granted. Upon receipt of therollback message the DS units may unlock the slice names associated withthe transaction identifier. Once the slice names have been unlocked, theDS units can then grant lock requests from other processing units forthe subject encoded data slices. The transaction identifier mayalternatively be replaced with a DS processing unit identifier if asingle DS processing unit does not make conflicting updates to a name.The transaction identifier would then not be provided in the persistenceand/or lock request messages, instead the distributed storage unitscould unlock based on names provided in the commit/rollback messages forlocks associated with a particular DS processing unit.

Advantages of the multi-phase lock request followed by the persistmessage include, but are not limited to, reduction of network trafficbased on encoded data slices not being sent when a lock is not achievedand a reduction of memory being used to hold encoded data slices until awrite commit can be granted.

Once persist messages have been received by a write threshold of DSunits one or more of the affected distributed storage units may fail tooverwrite the affected encoded data slices, in this case the one or moreDS processing units may abandon the update and an asynchronous agent canbe used to delete each of the involved updated encoded data slices,after which the asynchronous agent may delete the lock request. Thiswill ensure that partially written data objects are removed from the DSNmemory.

FIG. 14 is schematic block diagram of an embodiment of a dispersedstorage network (DSN) that illustrate steps of an example of updating adata object when competing devices are attempting to write to the samedistributed storage units of a dispersed storage network (DSN). The DSNincludes distributed storage (DS) client modules 1 and 2 and the network24 of FIG. 1, and a set of dispersed storage (DS) units 1-n. Each DSunit may be the DS execution unit 36 of FIG. 1. Each DS client moduleincludes the outbound DS processing 104 and the inbound DS processing106 of FIG. 3. Each DS unit includes the processing module 108 and thememory 112 of FIG. 3.

In the example of updating data, as illustrated in FIG. 14, the outboundDS processing 104 of a DS client module 1 receives an update requestregarding a data object A. The DS client module 1 sends a plurality oflock requests (660) to DS units 1-n. DS units 1-n grant the lockrequests depending on whether another processing unit has already beengranted a lock request for encoded data slices with the same slice name.DS units 1-n can then lock the indicated encoded data slices and send alock grant to DS client module 1. The DS client module 1, depending onwhether a write threshold of lock grants have been received from DSunits 1-n, can then transmit a persist message (680) to the DS unitsfrom which lock grants have been received.

It is noted that terminologies as may be used herein such as bit stream,stream, signal sequence, etc. (or their equivalents) have been usedinterchangeably to describe digital information whose contentcorresponds to any of a number of desired types (e.g., data, video,speech, audio, etc. any of which may generally be referred to as‘data’).

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “configured to”, “operably coupled to”, “coupled to”, and/or“coupling” includes direct coupling between items and/or indirectcoupling between items via an intervening item (e.g., an item includes,but is not limited to, a component, an element, a circuit, and/or amodule) where, for an example of indirect coupling, the intervening itemdoes not modify the information of a signal but may adjust its currentlevel, voltage level, and/or power level. As may further be used herein,inferred coupling (i.e., where one element is coupled to another elementby inference) includes direct and indirect coupling between two items inthe same manner as “coupled to”. As may even further be used herein, theterm “configured to”, “operable to”, “coupled to”, or “operably coupledto” indicates that an item includes one or more of power connections,input(s), output(s), etc., to perform, when activated, one or more itscorresponding functions and may further include inferred coupling to oneor more other items. As may still further be used herein, the term“associated with”, includes direct and/or indirect coupling of separateitems and/or one item being embedded within another item.

As may be used herein, the term “compares favorably”, indicates that acomparison between two or more items, signals, etc., provides a desiredrelationship. For example, when the desired relationship is that signal1 has a greater magnitude than signal 2, a favorable comparison may beachieved when the magnitude of signal 1 is greater than that of signal 2or when the magnitude of signal 2 is less than that of signal 1. As maybe used herein, the term “compares unfavorably”, indicates that acomparison between two or more items, signals, etc., fails to providethe desired relationship.

As may also be used herein, the terms “processing module”, “processingcircuit”, “processor”, and/or “processing unit” may be a singleprocessing device or a plurality of processing devices. Such aprocessing device may be a microprocessor, micro-controller, digitalsignal processor, microcomputer, central processing unit, fieldprogrammable gate array, programmable logic device, state machine, logiccircuitry, analog circuitry, digital circuitry, and/or any device thatmanipulates signals (analog and/or digital) based on hard coding of thecircuitry and/or operational instructions. The processing module,module, processing circuit, and/or processing unit may be, or furtherinclude, memory and/or an integrated memory element, which may be asingle memory device, a plurality of memory devices, and/or embeddedcircuitry of another processing module, module, processing circuit,and/or processing unit. Such a memory device may be a read-only memory,random access memory, volatile memory, non-volatile memory, staticmemory, dynamic memory, flash memory, cache memory, and/or any devicethat stores digital information. Note that if the processing module,module, processing circuit, and/or processing unit includes more thanone processing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,and/or processing unit implements one or more of its functions via astate machine, analog circuitry, digital circuitry, and/or logiccircuitry, the memory and/or memory element storing the correspondingoperational instructions may be embedded within, or external to, thecircuitry comprising the state machine, analog circuitry, digitalcircuitry, and/or logic circuitry. Still further note that, the memoryelement may store, and the processing module, module, processingcircuit, and/or processing unit executes, hard coded and/or operationalinstructions corresponding to at least some of the steps and/orfunctions illustrated in one or more of the Figures. Such a memorydevice or memory element can be included in an article of manufacture.

One or more embodiments have been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claims. Further, the boundariesof these functional building blocks have been arbitrarily defined forconvenience of description. Alternate boundaries could be defined aslong as the certain significant functions are appropriately performed.Similarly, flow diagram blocks may also have been arbitrarily definedherein to illustrate certain significant functionality.

To the extent used, the flow diagram block boundaries and sequence couldhave been defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claims. One of average skill in the art will alsorecognize that the functional building blocks, and other illustrativeblocks, modules and components herein, can be implemented as illustratedor by discrete components, application specific integrated circuits,processors executing appropriate software and the like or anycombination thereof.

In addition, a flow diagram may include a “start” and/or “continue”indication. The “start” and “continue” indications reflect that thesteps presented can optionally be incorporated in or otherwise used inconjunction with other routines. In this context, “start” indicates thebeginning of the first step presented and may be preceded by otheractivities not specifically shown. Further, the “continue” indicationreflects that the steps presented may be performed multiple times and/ormay be succeeded by other activities not specifically shown. Further,while a flow diagram indicates a particular ordering of steps, otherorderings are likewise possible provided that the principles ofcausality are maintained.

The one or more embodiments are used herein to illustrate one or moreaspects, one or more features, one or more concepts, and/or one or moreexamples. A physical embodiment of an apparatus, an article ofmanufacture, a machine, and/or of a process may include one or more ofthe aspects, features, concepts, examples, etc. described with referenceto one or more of the embodiments discussed herein. Further, from figureto figure, the embodiments may incorporate the same or similarly namedfunctions, steps, modules, etc. that may use the same or differentreference numbers and, as such, the functions, steps, modules, etc. maybe the same or similar functions, steps, modules, etc. or differentones.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of one or more of theembodiments. A module implements one or more functions via a device suchas a processor or other processing device or other hardware that mayinclude or operate in association with a memory that stores operationalinstructions. A module may operate independently and/or in conjunctionwith software and/or firmware. As also used herein, a module may containone or more sub-modules, each of which may be one or more modules.

As may further be used herein, a computer readable memory includes oneor more memory elements. A memory element may be a separate memorydevice, multiple memory devices, or a set of memory locations within amemory device. Such a memory device may be a read-only memory, randomaccess memory, volatile memory, non-volatile memory, static memory,dynamic memory, flash memory, cache memory, and/or any device thatstores digital information. The memory device may be in a form a solidstate memory, a hard drive memory, cloud memory, thumb drive, servermemory, computing device memory, and/or other physical medium forstoring digital information.

While particular combinations of various functions and features of theone or more embodiments have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent disclosure is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

1. A method for execution by one or more processing modules of one ormore computing devices of a dispersed storage network (DSN), the methodcomprises: determining that dispersed error encoded data slices storedin a plurality of distributed storage units of the DSN are to beupdated; sending a plurality of lock requests to the plurality ofdistributed storage units containing dispersed encoded data slicesdetermined to require updating; receiving a response from a writethreshold number of distributed storage units of the plurality ofdistributed storage units; and when the response from a write thresholdnumber of distributed storage units of the plurality of distributedstorage units indicates that a lock request has been granted by a firstwrite threshold number of distributed storage units, sending a persistmessage to a second write threshold number of distributed storage units.2. The method of claim 1, wherein each of the lock requests of theplurality of lock requests includes a slice name for a dispersed errorencoded data slice.
 3. The method of claim 1, wherein each of the lockrequests of the plurality of lock requests includes a transactionidentifier associated with the determining that a plurality ofdistributed storage units of the DSN is to be updated.
 4. The method ofclaim 1 further comprises; when the response from the write thresholdnumber of distributed storage units of the plurality of distributedstorage units indicates that a lock request has not been granted by eachof the write threshold number of distributed storage units, sending amessage to any of the write threshold number of distributed storageunits from which the lock request was granted that the lock grant shouldbe released.
 5. The method of claim 1, wherein the persist messageincludes dispersed error encoded data slices intended to be updated bythe one or more processing modules of the one or more computing devicesof the DSN.
 6. The method of claim 1 further comprises: receiving awrite threshold number of persist responses from the plurality ofdistributed storage units, wherein a persist response indicates that adistributed storage unit has been updated.
 7. The method of claim 4further comprises: receiving a message from a first distributed storageunit indicating that a second distributed storage unit has been granteda lock request for a same slice name.
 8. A computer readable memorycomprises: a first memory element that stores operational instructionsthat, when executed by a computing device of a dispersed storage network(DSN), causes the computing device to: determine that a plurality ofdistributed storage units of the DSN is to be updated; send a pluralityof lock requests to the plurality of distributed storage unitscontaining dispersed encoded data slices determined to require updating;receive a response from a write threshold number of distributed storageunits of the plurality of distributed storage units; and when theresponse from a write threshold number of distributed storage units ofthe plurality of distributed storage units indicates that a lock requesthas been granted by a first write threshold number of distributedstorage units, send a persist message to a second write threshold numberof distributed storage units.
 9. The computer readable memory of claim8, wherein each of the lock requests of the plurality of lock requestsincludes a slice name for a first distributed storage unit of theplurality of distributed storage units.
 10. The computer readable memoryof claim 8, wherein each of the lock requests of the plurality of lockrequests includes a transaction identifier associated with thedetermining that a plurality of distributed storage units of the DSN isto be updated.
 11. The computer readable memory of claim 8 furthercomprises; when the response from the write threshold number ofdistributed storage units of the plurality of distributed storage unitsindicates that a lock request has not been granted by each of the writethreshold number of distributed storage units, sending a message to anyof the write threshold number of distributed storage units from whichthe lock request was granted that the lock grant should be released. 12.The computer readable memory of claim 8, wherein the persist messageincludes data intended to be updated by the write threshold number ofdistributed storage units.
 13. The computer readable memory of claim 8further comprises: receiving a write threshold number of persistresponses from the plurality of distributed storage units, wherein apersist response indicates that a distributed storage unit has beenupdated.
 14. The computer readable memory of claim 8 further comprises:receiving a message from a first distributed storage unit indicatingthat a second distributed storage unit has been granted a lock requestfor a same slice name.
 15. A method for execution by a distributedstorage unit of a dispersed storage network (DSN), the method comprises:receiving a lock request from a distributed processing unit of adispersed storage network (DSN), wherein the lock request is associatedwith a determination that a dispersed error encoded data slice in thedistributed storage unit is to be updated; determining whether anotherdistributed processing unit has already been granted a lock request forthe dispersed error encoded data slice; and when another distributedprocessing unit has not already been granted a lock request for thedispersed error encoded data slice, sending a message to the distributedprocessing unit that the lock request has been granted for the dispersederror encoded data slice.
 16. The method of claim 15, wherein the lockrequest includes a slice name for the dispersed error encoded dataslice.
 17. The method of claim 15 further comprises: when anotherdistributed processing unit has already been granted a lock request forthe dispersed error encoded data slice, sending a message to thedistributed processing unit that the lock request will not be grantedfor the dispersed error encoded data slice.
 18. The method of claim 15further comprises: receiving a persist message from the distributedprocessing unit, wherein the persist message includes one or moredispersed error encoded data slices to be updated and a transactionidentifier; and unlocking a slice name for each of the dispersed errorencoded data slices associated with the transaction identifier.
 19. Themethod of claim 15 further comprises: receiving a message from thedistributed processing unit that the lock request that has been grantedshould be released, wherein the message that the distributed processingunit that the lock request that has been granted should be released isbased on the distributed processing unit not being granted a lockrequest by each of a write threshold number of distributed storageunits.